A Novel Approach for Workflow Scheduling in Hybrid Cloud with Dynamic Datacenter

Work process is used to speak to variety of use which requires huge data figuring and limit. To vanquish this need of data computation and limit dispersed processing has created as one of the best responses for on asks for resource provider. Nevertheless, on occasion the benefits open to us may not be satisfactory, so the need develops to gather more sources from various fogs. This is done by using the Hybrid cloud. Half and half cloud is mix of open and private cloud. The private cloud is guaranteed by the customer consequently there are no extra charges for using the benefits available in it, however open cloud is controlled by others so we have to pay for the using the advantage as indicated by the businesses. The USAge of the cream cloud offers adaptability to the customer. While using the half breed cloud, two most basic inquiries rises. The first is the best approach to segment the work procedure. In addition, the second one is the thing that benefit we need to get from individuals as a rule cloud so it can meet our essential inside the foreordained due date. The changed booking organization work handle for hybrid cloud give the less make span for the DAG than the main figuring and give us the best resources that we need to secure from open cloud to have enough planning vitality to arrange the work procedure inside given due date. We have gone through with two different approaches after scheduling has been performed to check the successful transaction between dynamic and static data center. We contemplated a hybrid approach which will reduce the complexity of the network but at the same time it also perform successful transaction between dynamic datacenters .Each time the transaction has been performed between different centers or clusters the consequences are successful

Evaluation of Metaverse Traffic Safety Implementations using fuzzy Einstein based logarithmic methodology of additive weights and TOPSIS method

As the Metaverse’s popularity grows, its effect on everyday problems is beginning to be discussed. The upcoming Metaverse world will influence the transportation system as cross-border lines blur due to rapid globalization. The purpose of this paper is to investigate the capabilities of the Metaverse and its alternatives to traffic safety, as well as to prioritize its advantages. The case study is based on a densely populated metropolis with an extensive education system. The city’s decision-makers will have to weigh the pros and cons of the Metaverse’s effect on traffic safety. To illustrate the complex forces that drive the decision-making process in traffic safety, we create a case study with four alternatives to Metaverse’s integration into the traffic system. Alternatives are evaluated using twelve criteria that reflect the decision problem’s rules and regulations, technology, socioeconomic, and traffic aspects. In this study, fuzzy Einstein based logarithmic methodology of additive weights (LMAW) is applied to calculate the weights of the criteria. We present a new framework that combines Einstein norms and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the alternatives. The findings of this study show that public transportation is the most appropriate area for implementing the Metaverse into traffic safety because of its practical opportunities and broad usage area

Guest Editorial Artificial Intelligence and Deep Learning for Intelligent and Sustainable Traffic and Vehicle Management (VANETs)

Intelligence and sustainability are two essential drivers for the development of current and future Intelligent Transportation Systems. On one hand, the complexity of vehicular ecosystems and the inherently risk-prone circumstances under which pedestrian and vehicles coexist call for the endowment of intelligent functionalities in almost all systems and processes participating in such ecosystems. On the other hand, risk may be the most important objective to be guaranteed by the provision of intelligence in ITS, but it is not certainly the only one: when safety is assured, sustainability comes into play, seeking to convey intelligence to the distinct parts composing the ITS landscape with efficiency, minimum carbon footprint, wastage of resources or any other factor affected by the technological empowerment itself

ThinORAM: Towards Practical Oblivious Data Access in Fog Computing Environment

Oblivious RAM (ORAM) is important for applications that require hiding of access patterns. However, most of existing implementations of ORAM are very expensive, which are infeasible to be deployed in lightweight devices, likethe gateway devices as fog nodes. In this paper, we focus on how to apply the expensive ORAM to protect access pattern in lightweight devices and propose an ORAM scheme supporting thin-client, called “ThinORAM”, under non-colluding clouds. Our proposed scheme removes complicated computations in the client side and requires only O (1) communication cost with a reasonable response time. We further show how to securely deploy ThinORAM in the fog computing environment to achieve oblivious data access with minimum client cost. Experiments show that our scheme can eliminate most of the client storage and reduce the cloud-cloud bandwidth by 2 ×, with 2 × faster response time, when compared to the best scheme that aims at reducing client side overheads

Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

Abstract Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60]).</jats:p

Implementation of corticosteroids in treating COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK:prospective observational cohort study

BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. FUNDING: UK National Institute for Health Research and UK Medical Research Council